Poster + Paper
10 April 2023 Lamina landmark detection in ultrasound images: a preliminary study
Sen Li, Lou Gauthier, Farida Cheriet, Carole Fortin, Philippe Paquette, Catherine Laporte
Author Affiliations +
Conference Poster
Abstract
Freehand (FH) 3D ultrasound (US) imaging is emerging as a promising modality for spine imaging because it is non-invasive and inexpensive. Among the vertebral landmarks that can be used to represent the spine, paired laminae can play a vital role in a transverse scan for 3D spine deformity analysis by providing symmetry information. However, there is currently no laminae landmark recognition algorithm that has been tested on poor-quality 2D US scans. In this study, we propose a deep learning framework to automatically and simultaneously assess the presence of two laminae and estimate their landmark coordinates for the purpose of live US-based assessment of spine shape. To label the training data, we propose a labeling protocol based on a weight distribution on the virtual bone surface to make the pixel representative most likely the closest pixel to the spinal cord. In total, 6 FH 3D US sequences of the spine covering vertebrae T1 to L5 were collected from 3 participants. They were labeled based on the proposed protocol and validated by two spine ultrasound experts. The performance of the deep learning-based lamina landmark detection method was assessed through K-Fold cross-validation, with results reaching a mean distance error of 2.1 ± 1.3(mm) and 1.8 ± 1.2(mm) in true-positive images for left and right lamina landmarks respectively. Our method could allow for live laminae landmark extraction during clinical US spine exams, which would be useful for spinal ultrasound image interpretation, vertebral level identification, and spine deformity analysis in 3D based on paired laminae landmarks projected on three anatomical planes.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sen Li, Lou Gauthier, Farida Cheriet, Carole Fortin, Philippe Paquette, and Catherine Laporte "Lamina landmark detection in ultrasound images: a preliminary study", Proc. SPIE 12470, Medical Imaging 2023: Ultrasonic Imaging and Tomography, 1247011 (10 April 2023); https://doi.org/10.1117/12.2653277
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KEYWORDS
Spine

Ultrasonography

Bone

Surface plasmons

Cross validation

Deformation

Deep learning

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